Indian International Conference on Artificial Intelligence最新文献

On Comparative Analogy between Ant Colony Systems and Neural Networks Considering Behavioral Learning Performance 考虑行为学习性能的蚁群系统与神经网络的比较类比

Indian International Conference on Artificial Intelligence Pub Date : 2015-06-27 DOI: 10.12691/JCSA-3-3-4

H. Mustafa, A. Al-Hamadi

{"title":"On Comparative Analogy between Ant Colony Systems and Neural Networks Considering Behavioral Learning Performance","authors":"H. Mustafa, A. Al-Hamadi","doi":"10.12691/JCSA-3-3-4","DOIUrl":"https://doi.org/10.12691/JCSA-3-3-4","url":null,"abstract":"This article addresses an interesting comparative analytical study. The presented study considers two concepts of diverse algorithmic biological behavioral learning approach. Those concepts for computational intelligence are tightly related to neural and non-neural Systems. Respectively, the first algorithmic intelligent approach concerned with observed obtained practical results after three neural animal systems’ activities. Namely, they are Pavlov’s, and Thorndike’s experimental work. Furthermore, a mouse’s trials during its movement inside figure of eight (8) maze, those aiming to reach optimal solution for reconstruction problem. However, second algorithmic intelligent approach conversely originated from observed activities’ results for non-neural Ant Colony System (ACS). Those results have been obtained after reaching optimal solution solving Traveling Sales-man Problem (TSP). Interestingly, the effect of increasing number of agents (either neurons or ants) on learning performance shown to be similar for both introduced neural and non-neural systems. Considering observed two systems' performances, it has shown both to be in agreement with learning convergence process searching for Least Mean Square (LMS) error algorithm. Accordingly, adopted ANN modeling is realistically relevant tool systematic observations' investigation and performance analysis for both selected computational intelligence (biological behavioral learning) systems.","PeriodicalId":262638,"journal":{"name":"Indian International Conference on Artificial Intelligence","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123875477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

On Web-based Support Systems 网上支援系统

Indian International Conference on Artificial Intelligence Pub Date : 2010-03-31 DOI: 10.1007/978-1-84882-628-1

Jingtao Yao

引用次数: 61

Strategy proof electronic markets 策略证明电子市场

Indian International Conference on Artificial Intelligence Pub Date : 2007-08-19 DOI: 10.1145/1282100.1282110

A. Dani, A. K. Pujari, V. Gulati

{"title":"Strategy proof electronic markets","authors":"A. Dani, A. K. Pujari, V. Gulati","doi":"10.1145/1282100.1282110","DOIUrl":"https://doi.org/10.1145/1282100.1282110","url":null,"abstract":"In electronic double auctions, property of incentive compatibility is very important. Incentive compatibility ensures that truthful bidding is the dominant strategy. Other important properties in electronic auctions are budget balance (BB) and individual rational (IR). The former ensures that the auction does not run in loss whereas the latter ensures voluntary participation. However these can be achieved only after sacrificing efficiency. The mechanisms based on uniform clearing price have been proposed in literature. Such mechanisms satisfy the properties of BB and IR. They are incentive compatible. However uniform price auction mechanism suffers from the problem of demand shading. Due to demand reduction, agents can acquire units at a lower price. This affects the property of incentive compatibility. Another problem with this approach is that it is not false name proof, meaning that agents can submit bids under different names to improve their utility. In electronic markets, where bids and asks are submitted remotely this property is very important. In this paper we propose discriminatory price mechanism, which is strategy proof, individually rational and budget balance. It is also false name proof, meaning agents cannot improve their utility by submitting false name bids.","PeriodicalId":262638,"journal":{"name":"Indian International Conference on Artificial Intelligence","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133693623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Prediction of first lactation 305-day milk yield based on weekly test day records using artificial neural networks in Sahiwal Cattle 基于周试验日记录的人工神经网络预测萨希瓦尔牛首次泌乳305天产奶量

Indian International Conference on Artificial Intelligence Pub Date : 1900-01-01 DOI: 10.5146/IJDS.V65I3.25895.G11927

B. DongreV., R. S. Gandhi, A. P. Ruhil, K. GuptaR., K. SinghR.

引用次数: 9

A Framework for Synthesizing Arbitrary Boolean Expressions Induced by Frequent Itemsets 频繁项集诱导的任意布尔表达式的合成框架

Indian International Conference on Artificial Intelligence Pub Date : 1900-01-01 DOI: 10.1007/978-3-319-13212-9_3

A. Adhikari, Jhimli Adhikari

引用次数: 10